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Florian BRUNIAUX fd17414abb docs: add AI productivity research, trust calibration, and exploration workflow 
## New Content

### Trust & Verification (ultimate-guide.md)
- Section 1.7 "Trust Calibration: When and How Much to Verify" (~155 lines)
  - Research-backed stats (ACM, Veracode, CodeRabbit, Cortex.io)
  - Verification spectrum by code type
  - Solo vs Team strategies with workflow diagrams
  - "Prove It Works" checklist
- New pitfall: "Trust AI output without proportional verification"
- CLAUDE.md size guideline: 4-8KB optimal, >16K degrades coherence

### AI Productivity (learning-with-ai.md)
- Section "The Reality of AI Productivity" (~55 lines)
  - Productivity curve phases (Wow Effect → Targeted Gains → Plateau)
  - High-gain vs low/negative-gain task categorization
  - Team success factors
- Productivity trajectory table by pattern (Dependent/Avoidant/Augmented)
- 5 new sources (GitHub, McKinsey, Stack Overflow, Uplevel, DORA)

### Session Limits (architecture.md)
- "Session Degradation Limits" section
  - Turn limits (15-25), token thresholds (80-100K)
  - Success rates by scope (1-3 files: ~85%, 8+ files: ~40%)

### Exploration Workflow
- NEW: guide/workflows/exploration-workflow.md
  - Anti-anchoring prompts, 3-5 approaches pattern
- iterative-refinement.md: Script Generation Workflow (3-7 iteration pattern)
- anchor-catalog.md: Anti-Anchoring Techniques, Exploration/Iteration Prompts

### Reference Updates
- adoption-approaches.md: Empirical data section
- reference.yaml: New deep_dive entries, updated line numbers

Sources: MetalBear engineering blog, arXiv studies, Addy Osmani (Jan 2026)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-19 19:16:33 +01:00
..
claude-code-releases.yaml docs: add behavior category to breaking_summary 2026-01-19 10:18:25 +01:00
llms.txt feat: add ecosystem positioning, install script & new commands 2026-01-19 08:42:33 +01:00
README.md refactor: restructure repo into thematic directories v3.1.0 2026-01-13 15:30:02 +01:00
reference.yaml docs: add AI productivity research, trust calibration, and exploration workflow 2026-01-19 19:16:33 +01:00

README.md

Machine-Readable References

Files optimized for LLM/AI consumption.

Contents

File Description Tokens
reference.yaml Structured index with line numbers for deep dives ~2K
llms.txt Standard LLM context file for repository indexation ~1.5K

Usage

Give Claude Code instant expertise

# Paste into any AI assistant
curl -sL https://raw.githubusercontent.com/FlorianBruniaux/claude-code-ultimate-guide/main/machine-readable/reference.yaml

Reference in Claude Code

@machine-readable/reference.yaml

Add to system prompts

Include the YAML content in your AI assistant's system prompt for Claude Code expertise.

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